APIs

Embeddings

llm.buzz serves embeddings models on the OpenAI Embeddings API, so the OpenAI and OpenRouter SDKs reach them with the base URL alone. Chat Completions, Responses and Messages refuse an embeddings model with a 400 on model that names POST /api/v1/embeddings.

On this page

Find an embeddings model Create embeddings Billing Not supported

The route takes your key as a bearer token, as every other model route does (Authentication).

Find an embeddings model

GET https://api.llm.buzz/api/v1/models leaves embeddings models out by default: output_modalities=embeddings lists them, and output_modalities=all lists every model. GET https://api.llm.buzz/api/v1/embeddings/models is the same list with that filter fixed, paged with limit and offset. With your key, both list the embeddings models your key can call; without a key, the public ones.

curl https://api.llm.buzz/api/v1/embeddings/models

An embeddings model lists as text->embeddings with its context window. pricing.prompt is its input price in US dollars per token, at your rate, and pricing.completion is "0": an embeddings call has no output to bill.

The Models page lists embeddings models too, and its Output filter picks them out. Each one's page shows its input price per million tokens and its Dimensions: the length of the vectors a request without dimensions gets.

Create embeddings

POST https://api.llm.buzz/api/v1/embeddings takes the OpenAI Embeddings API's body and answers in its shape.

from openai import OpenAI
import os

client = OpenAI(
    base_url="https://api.llm.buzz/api/v1",
    api_key=os.environ["LLM_BUZZ_KEY"],
)
result = client.embeddings.create(
    model="qwen/qwen3-embedding-8b",
    input=["first passage", "second passage"],
)
print(len(result.data), len(result.data[0].embedding))

curl https://api.llm.buzz/api/v1/embeddings \
  -H "Authorization: Bearer $LLM_BUZZ_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "qwen/qwen3-embedding-8b", "input": ["first passage", "second passage"]}'

Field	Rule
`model`	Required: an embeddings model. Another model is a 400 `unsupported_capability` on `model`.
`input`	Required: a string, a list of strings, a list of token IDs, or a list of such lists, none of them empty. A flat list of token IDs gets one vector. Token IDs go to the provider unchanged, so they must match the model's tokenizer.
`encoding_format`	`float` or `base64`: how the vectors come back.
`dimensions`	Sent to the provider as you give it. Without it, the vectors have the model's Dimensions.
`provider`	Steers the request as on chat; see Provider preferences.
`user`	Recorded as the end-user label, and not sent to the provider.
`stream`	Leave it out or send `false`. Embeddings are never streamed, and `true` is a 400.

Fields the route does not know are dropped. The route keeps no answers and ignores an Idempotency-Key header, so a retry is a new call, billed again.

The answer:

{"object": "list", "data": [{"object": "embedding", "index": 0, "embedding": [0.0123, -0.0456]}],
 "model": "qwen/qwen3-embedding-8b", "provider": "DeepInfra",
 "usage": {"prompt_tokens": 4, "total_tokens": 4, "cost": 4e-8}}

The vectors are the provider's own, one per input. usage.prompt_tokens is the input tokens the provider counted, which the call bills, and usage.cost is the call's price in US dollars at your rate. provider names the provider that answered.

Billing

An embeddings call bills the input tokens its provider reports, usage.prompt_tokens, at that provider's input price and your rate. It has no output price. Your credit, budgets and key limits apply as on chat; Errors lists the 402 and 403 answers.

A call that fails over to another provider bills only the provider that answered.
A call bills nothing when its provider answered an error, or never received the request (the connection was refused, or DNS or TLS failed).
A timeout, a network fault after the request was sent, or your client disconnecting bills what llm.buzz reserved for the call before calling the provider, since the provider may have done the work and billed it.

Not supported

Image or other multimodal input to an embeddings model, streaming, and embeddings models in the console's Playground.